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The Fallacy of Seeing Patterns
- bognition 10y ago>As an analyst, one needs to keep in mind that the Journey is more important than reaching the Destination. I'm really not sure what to make of the last line. The goal of analysis should be to produce results that are actionable. In the end it should matter very little how they are obtained as long as they are accurate.
- apathy 10y agoAccurate results are not necessarily actionable.
- RA_Fisher 10y agoA lot of times an action is the product of many analyses that individually aren't actionable. To me it's similar to managing fixed vs. variable costs. You've got to make investments of various size, but the payoff needs to correspond to the investment.
- ACow_Adonis 10y agoWell, as an analyst looking forward to finding future jobs, its often more important :P
- hinkley 10y agoThis is the road to metric dysfunction. Or at least, if you continue to use the metric that diagnosed the problem while trying to address it, you're going to get what you measure. With most groups I've been with, they were relieved to get the metrics good enough to detect anything at all, and don't have the stamina to come up with a more accurate way to determine the same thing.
- doctorpangloss 10y ago> In the end it should matter very little how they are obtained as long as they are accurate. That's about as actionable of a statement as a CEO telling you he wants you to do whatever "will be the most successful." Well duh :)
- apathy 10y agoCtrl-F "apophenia" 0 matches on this page Welp, that's pretty sad. https://en.wikipedia.org/wiki/Apophenia https://en.wikipedia.org/wiki/Apophenia
- liquidise 10y agoExcellent link, but no need to poopoo a post because the author's vocab didn't include a word you expected.
- apathy 10y agoWords and concepts exist for a reason. The author of the post could have turned up the (well researched and imho fascinating) antecedent work very quickly simply by googling his piece's title. That he did not makes me sad. Very smart people have previously studied most interesting problems. Ignoring their work is both arrogant and foolish. Put differently, you don't learn much by talking, but you learn a lot by listening. You learn a little by writing, but you and your readers learn much more if you read up first. (I am not assuming you wrote this. The themes are general.) If I wrote a piece that ignored a decades-old, well-known, fundamental result, not only would editors and colleagues slam me for it, I'd be ashamed of it myself. I went back and skimmed a few more of this author's posts and I have to say, they're not of a quality I would suggest to students. If they happen to read this, I hope they'll talk with someone who has a little formal training and revise their work.
- jsprogrammer 10y agoDoes joining the Nazi party qualify you as being very smart? Wikipedia references work [0] that indicates Konrad's theory could not be validated empirically. Do you have any references that validate what you are claiming as a well-known, fundamental result? Can you give a definition of the theory? [0] https://www.thieme-connect.com/DOI/DOI?10.1055/s-2007-999113 https://www.thieme-connect.com/DOI/DOI?10.1055/s-2007-999113
- apathy 10y ago
- auvi 10y agoCan anybody reading this comment please enlighten me on good algorithms for optimum bin sizes for histograms? I have tried DW Scott's (1979) method. But are there any new better kid in the block?
- Glimjaur 10y agoI'm by no means an expert in the area, but i know that the Freedman-Diaconis rule (https://en.wikipedia.org/wiki/Freedman%E2%80%93Diaconis_rule https://en.wikipedia.org/wiki/Freedman%E2%80%93Diaconis_rule) is used by the seaborn Python plotting library (https://web.stanford.edu/~mwaskom/software/seaborn/index.html https://web.stanford.edu/~mwaskom/software/seaborn/index.htm...) which seems to consistently produce good results.
- xapata 10y agoThere is no free lunch. You must know something about your data -- use your intuition.
- iaw 10y agoI wish the article was on Apophenia, it would be more fun. Instead it's not clear to me who the target audience is. The phrasing makes it appear to be targeted at analysts and not their business partners. Assuming that to be the case, senior analysts are substantially beyond the level this article is written at (or should be). Entry level analysts need close supervision to prevent them from making these, and other, mistakes. The examples the author draws (specifically cheese vs. infant mortality and the google flu approximations) don't do a good job at identifying when this issue arises. For the cheese example it's unclear if the phenomenon is real or not (the magnitude of the variation in infant death may actually be significant, if the cheese consumption variation was small then there would be a different story). The author does nothing to help the reader resolve this. In the Google flu example it's only through hindsight (and colossal failure) that the author identifies the lack of validity in Google's model. I agree 100% with his point but I don't think the article is providing much value because essentially the author is simply saying: "be aware, this type of problem exists out there..." without providing information necessary to navigate/resolve the problem.
- jrapdx3 10y agoThe article starts with, "Human beings try to find patterns to explain the reason behind almost every phenomenon, but that doesn’t mean that there is a pattern to rely on." The second part of the sentence is true, on further observation some patterns prove not to be patterns. However the first half, the attempt to explain why we "find patterns" isn't convincing. Instead, replace that phrase with this: "based on brain construction, we humans are predisposed to find patterns in data we encounter". This idea holds up to evolutionary scrutiny, organisms have mechanisms biased for self-protection and finding food and other resources through various forms of pattern recognition. IOW we find patterns we're neurologically capable of finding, particularly in regard to survival and reproduction. Perhaps it's more accurate to assert we "find patterns" useful in making predictions about our present and future state within the environments we occupy. The fact that patterns may not turn out to be authentic is simply part of a process of refinement of pattern-seeking and improving value as predictors of future states. We may call a pattern an "explanation" but nothing is actually "explained" as shown by the fact we reserve the right to enhance or revise the "pattern", or what we insist it predicts, at any given time. Edits: grammar and clarity
- Retra 10y agoOur brains are basically built to do pattern matching. Though, truthfully, I find that is too abstract of a way of putting it, and in fact, people tend to associate "meaning" with "pattern" and thus you end up with statements like that one. What I would say the brain is good at is finding patterns in terms of identifying what is appropriate, with a particularly general understanding of "appropriate." There's a huge evolutionary drive for this. It's a bit disjointed to say wolves howl with each other because "brains detect patterns" and somehow find them useful. It's much clearer when we say that "brains encode patterns in terms of appropriateness", and thus wolves howl with each other because their brains know it is appropriate to do so. Just like germ's biology encodes that it's appropriate to wiggle harder in salty water, or how a person knows that certain words are correct in specific situations. So our brains are more like engines for mapping patterned associations to feelings of appropriateness in context.
- jrapdx3 10y ago
- T0T0R0 10y agoI really thought this was going to be a rant harping on object-oriented programming.
- rrecuero 10y agoOur brains are wired to believe a plausible story easier than the one told by the base rate or stats... We need to be aware of the gaps our brain fills by itself. Definitely not easy, though...